Galvanalyser is a system for automatically storing data generated by battery cycling machines in a database

Galvanalyser is a system for automatically storing data generated by battery cycling machines in a database, using a set of "harvesters", whose job it is to monitor the datafiles produced by the battery testers and upload it in a standard format to the server database. The server database is a relational database that stores each dataset along with information about column types, units, and other relevant metadata (e.g. cell information, owner, purpose of the experiment)

There are two user interfaces to the system:

• a web app front-end that can be used to view the stored datasets, manage the harvesters, and input metadata for each dataset
• a REST API which can be used to download dataset metadata and the data itself. This API conforms to the battery-api OpenAPI specification, so tools based on this specification (e.g. the Python client) can use the API.

A diagram of the logical structure of the system is shown below. The arrows indicate the direction of data flow.

Project documentation

The documentation directory contains more detailed documentation on a number of topics. It contains the following items:

• FirstTimeQuickSetup.md - A quick start guide to setting up your first complete Galvanalyser system
• AdministrationGuide.md - A guide to performing administration tasks such as creating users and setting up harvesters
• DevelopmentGuide.md - A guide for developers on Galvanalyser
• ProjectStructure.md - An overview of the project folder structure to guide developers to the locations of the various parts of the project

Technology used

This section provides a brief overview of the technology used to implement the different parts of the project.

Docker

Dockerfiles are provided to run all components of this project in containers. A docker-compose file exists to simplify starting the complete server side system including the database, the web app and the Nginx server. All components of the project can be run natively, however using Docker simplifies this greatly.

A Docker container is also used for building the web app and its dependencies to simplify cross platform deployment and ensure a consistent and reliable build process.

Backend server

The server is a Flask web application, which uses SQLAlchemy and psycopg2 to interface with the Postgres database.

Harvesters

The harvesters are python modules in the backend server which monitor directories for tester datafiles, parse them according to the their format and write the data and any metadata into the Postgres database. The running of the harvesters, either periodically or manually by a user, is done using a Celery distributed task queue.

Frontend web application

The frontend is written using Javascript, the React framework and using Material-UI components.

Database

The project uses PostgreSQL for its database. Other databases are currently not supported. An entity relationship diagram is shown below.